Skill UI

A comprehensive guide and set of tools for programmatically building, scaffolding, and deploying Power Automate cloud flows using the FlowStudio MCP server. It guides agents through the entire workflow, including checking for existing flows, resolving connection references, defining actions, and final deployment/testing, all without needing to open the portal.

This comprehensive guide provides step-by-step instructions for setting up a development environment to use AWS CDK (Cloud Development Kit) with Python. It covers installing prerequisites (Node.js, AWS CLI), initializing a CDK project, managing Python dependencies, and mastering the full deployment workflow, enabling users to define and deploy scalable AWS infrastructure as code.

This toolkit provides comprehensive automation capabilities for Box cloud storage. It allows users to manage the entire document lifecycle, including file uploading and downloading, deep content searching using metadata filters, creating and modifying folders, and managing collaboration permissions. Ideal for integrating Box into automated business workflows, ensuring documents are always accessible and organized.

This skill provides advanced debugging capabilities for failing Power Automate cloud flows using the FlowStudio MCP server. Unlike the limited status codes from the standard Graph API, this tool gives agents deep, action-level inputs and outputs, allowing users to find the true root cause of failures. It is essential for diagnosing complex issues like expression failures, connector authentication errors, or internal run errors.

This skill provides comprehensive automation for managing OneDrive file lifecycles. Users can perform advanced operations including searching across metadata and content, uploading and downloading files, organizing folders, creating share links, and granularly managing permissions for specific users. It utilizes a structured workflow approach via Rube MCP, making it ideal for automating business processes involving cloud document storage and collaboration.

This skill guides the management of CI/CD pipelines within KubeSphere DevOps. It utilizes Kubernetes Custom Resources (CRs) to define, trigger, and monitor complex build workflows, seamlessly integrating with Jenkins concepts in a cloud-native manner. Use it for automating build, test, and deployment processes for applications running on Kubernetes.

This runbook provides systematic procedures for diagnosing and resolving common automation failures specific to Apple Notes on macOS. It covers critical local issues like app crashes, iCloud sync failures, TCC permission revocations, and database corruption, following a comprehensive detect-diagnose-fix-verify cycle. Essential for maintaining reliable Notes automation workflows.

This utility provides a structured way to manage and separate notes across multiple accounts and environments within Apple Notes. By utilizing distinct accounts (e.g., iCloud for Production, 'On My Mac' for Development), users can ensure absolute data isolation between development, staging, and live production data. It is crucial for maintaining clean separation in complex development workflows and QA testing scenarios.

Automate the entire deployment lifecycle for ML inference services on CoreWeave GPU cloud. This workflow integrates unit testing, container image building (to GHCR), and rolling deployment to CoreWeave Kubernetes clusters via GitHub Actions. Ideal for ensuring stable, high-performance deployment of GPU-dependent models. Key features include validating GPU manifest requests and managing deployments using standard Kubernetes APIs.

A comprehensive guide and set of tools for establishing a local development workflow tailored for CoreWeave GPU deployments. This includes steps for building Docker containers, validating Kubernetes YAML manifests using dry-run, and managing the full deployment lifecycle for AI inference services before pushing to the cloud.

This skill guides the setup and configuration of the CAST AI Workload Autoscaler, enabling dynamic right-sizing of pod resource requests (CPU and Memory). It automatically adjusts resources based on actual usage, significantly reducing cloud over-provisioning costs. Use this guide to implement workload scaling policies, configure resource limits via Kubernetes annotations, and monitor scaling events in Kubernetes environments.

This skill provides blueprints for deploying Clari data export pipelines into robust, production-grade cloud environments. It guides users on setting up reliable, scheduled, and serverless data syncs using major platforms like Airflow DAGs, AWS Lambda, and Google Cloud Functions. Ideal for automating revenue forecasting and business intelligence data extraction.